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Tracking**: Real-time progress bars and detailed logs\n- 📝 **Comprehensive Reports**: Markdown + JSON reports with deployment recommendations\n\n---\n\n## Installation\n\n### Option 1: npm (Global Installation)\n\n```bash\ncd /path/to/sip-benchmark\nnpm install\nnpm link\n```\n\nNow you can use `sip-benchmark` from anywhere!\n\n### Option 2: npm (Local to Web App)\n\n```bash\ncd /path/to/sip-ai\nnpm install --save-dev /path/to/sip-benchmark\n```\n\nThen use via `npx`:\n```bash\nnpx sip-benchmark <command>\n```\n\n### Option 3: Direct Execution (No Installation)\n\n```bash\ncd /path/to/sip-ai\nnode /path/to/sip-benchmark/bin/cli.js <command>\n```\n\n---\n\n## Requirements\n\n1. **Sip-AI Web App**: This tool must be run from within the Sip-AI web app directory\n2. **Environment Setup**: `.env.local` must be configured with:\n   - `POSTGRES_URL` - Database connection\n   - `OPENAI_API_KEY` - For agent and embeddings\n   - `YOUTUBE_API_KEY` - For scraping channels\n   - Other API keys as needed (Anthropic, Gemini, Langfuse, etc.)\n3. **Dependencies**: Web app dependencies must be installed (`npm install`)\n\n---\n\n## Usage\n\n### Quick Start (Interactive Menu)\n\nThe easiest way to use the tool is with the interactive menu:\n\n```bash\ncd /path/to/sip-ai\nsip-benchmark menu\n```\n\nThis launches a user-friendly guided interface with options for:\n- Quick Test (paste URL → auto-create → run → report)\n- Create Benchmark Suite\n- Run Benchmark\n- View Reports\n- List Benchmarks\n\n### Command-Line Interface\n\n#### 1. Create a Benchmark Suite\n\n```bash\nsip-benchmark setup \\\n  --name \"My Benchmark\" \\\n  --channels \"UCxxx,UCyyy\" \\\n  --cases-per-tier 5\n```\n\n**Options:**\n- `--name` (required): Benchmark name\n- `--channels` (required): Comma-separated channel IDs or YouTube URLs\n- `--cases-per-tier` (optional): Test cases per performance tier (default: 5)\n- `--description` (optional): Benchmark description\n\n**What it does:**\n- Samples high-performing (top 25%) and low-performing (bottom 25%) videos\n- Generates test cases with ground truth metrics (view percentile, engagement, sentiment)\n- Creates idea descriptions from video title + description + transcript\n- Stores test cases in database for reuse\n\n#### 2. Run a Benchmark\n\n```bash\nsip-benchmark run --benchmark-id <uuid>\n```\n\n**Options:**\n- `--benchmark-id` (required): Benchmark UUID to run\n- `--model` (optional): Model to use (default: from env or gpt-4.1-2025-04-14)\n- `--temperature` (optional): Temperature (default: 0.7)\n- `--skip-persona-regen` (optional): Use cached personas instead of regenerating\n\n**What it does:**\n- Regenerates personas for all channels (by default)\n- Runs IdeaEvaluationAgent (Steps 3-6) on all test cases\n- Evaluates predictions with LLM judge (3 dimensions)\n- Calculates statistics (mean, SD, p-value vs baseline)\n- Generates markdown + JSON reports in `reports/` directory\n\n#### 3. List Benchmarks\n\n```bash\nsip-benchmark list\n```\n\nShows all benchmarks with test case counts and run history.\n\n#### 4. View Report\n\n```bash\nsip-benchmark report --run-id <uuid>\n```\n\nDisplays a summary of a benchmark run with statistics and recommendations.\n\n---\n\n## How It Works\n\n### Architecture\n\nThe tool is a **lightweight wrapper** that:\n1. Detects the Sip-AI web app directory\n2. Loads `.env.local` environment variables\n3. Validates required environment variables\n4. Calls the web app's `npm run benchmark:*` scripts\n5. Uses the **exact production code** for testing (no mocking)\n\n### Test Flow\n\n```\n┌─────────────────────────────────────────────────┐\n│ 1. Setup: Sample Videos + Generate Test Cases  │\n└─────────────────┬───────────────────────────────┘\n                  │\n                  ▼\n┌─────────────────────────────────────────────────┐\n│ 2. Run: Regenerate Personas (optional)         │\n└─────────────────┬───────────────────────────────┘\n                  │\n                  ▼\n┌─────────────────────────────────────────────────┐\n│ 3. Run: Execute Agent on All Test Cases        │\n│    - Topic Fit Score (Step 3)                  │\n│    - Audience Resonance (Step 4)               │\n│    - Risk Assessment (Step 5)                  │\n│    - Final Report (Step 6)                     │\n└─────────────────┬───────────────────────────────┘\n                  │\n                  ▼\n┌─────────────────────────────────────────────────┐\n│ 4. Judge: Evaluate Predictions vs Reality      │\n│    - Directional Accuracy (40%)                │\n│    - Verdict Alignment (40%)                   │\n│    - Internal Consistency (20%)                │\n└─────────────────┬───────────────────────────────┘\n                  │\n                  ▼\n┌─────────────────────────────────────────────────┐\n│ 5. Analyze: Calculate Statistics               │\n│    - Olympic-trimmed mean                      │\n│    - Two-sample t-test vs baseline             │\n│    - Cohen's d effect size                     │\n└─────────────────┬───────────────────────────────┘\n                  │\n                  ▼\n┌─────────────────────────────────────────────────┐\n│ 6. Report: Generate Markdown + JSON            │\n│    - Statistics summary                        │\n│    - Deployment recommendation                 │\n│    - Individual test case results              │\n└─────────────────────────────────────────────────┘\n```\n\n---\n\n## Workflow Example\n\n### Scenario: Test a New Prompt Version\n\n```bash\n# 1. Create benchmark suite (one-time setup)\ncd /path/to/sip-ai\nsip-benchmark setup \\\n  --name \"Tech Channels Q1 2025\" \\\n  --channels \"UCxxx,UCyyy,UCzzz\" \\\n  --cases-per-tier 10\n\n# Output: Benchmark ID: abc123...\n\n# 2. Run baseline (with current production prompts)\nsip-benchmark run --benchmark-id abc123\n\n# Output:\n#   Mean Score: 7.23\n#   Baseline established!\n\n# 3. Edit prompts in Langfuse (label: \"experimental\")\n# Visit Langfuse UI → Update prompts → Label as \"experimental\"\n\n# 4. Run comparison (with new experimental prompts)\nLANGFUSE_PROMPT_LABEL=experimental sip-benchmark run --benchmark-id abc123\n\n# Output:\n#   Mean Score: 8.45\n#   P-value: 0.0023 (significant improvement!)\n#   Cohen's d: 0.82 (large effect size)\n#   Recommendation: DEPLOY - Significant improvement detected\n\n# 5. View full report\nsip-benchmark report --run-id <latest-run-id>\n\n# 6. If satisfied, promote prompts to production in Langfuse UI\n```\n\n---\n\n## Configuration\n\n### Environment Variables\n\nThe tool uses the web app's `.env.local` automatically. Required variables:\n\n```bash\n# Database (Required)\nPOSTGRES_URL=postgres://...\n\n# LLM APIs (Required)\nOPENAI_API_KEY=sk-...\nYOUTUBE_API_KEY=...\n\n# Optional (uses defaults if not set)\nLLM_MODEL=gpt-4.1-2025-04-14\nMAML_MODEL=gpt-4o\nANTHROPIC_API_KEY=...\nGOOGLE_GEMINI_API_KEY=...\n\n# Langfuse (Optional - for prompt management)\nLANGFUSE_PUBLIC_KEY=pk-...\nLANGFUSE_SECRET_KEY=sk-...\nLANGFUSE_PRODUCTION_PUBLIC_KEY=pk-...\nLANGFUSE_PRODUCTION_SECRET_KEY=sk-...\nLANGFUSE_PROMPT_LABEL=experimental\n```\n\n### Benchmark Mode\n\nWhen running benchmarks, the tool automatically sets:\n```bash\nBENCHMARK_MODE=true\n```\n\nThis suppresses verbose logs for cleaner progress bars during parallel execution.\n\n---\n\n## Performance & Costs\n\n### Speed (with parallel execution)\n- **Setup**: ~5 min per channel (one-time)\n- **Run (18 test cases, 3 channels)**:\n  - With persona regen: ~3-6 minutes\n  - Without persona regen: ~2-4 minutes\n\n### Costs (OpenAI API)\n- **Setup**: $0.60-$1.20 per channel (one-time)\n- **Run with personas**: $4-$7 for 30 test cases\n- **Run without personas**: $2-$4.50 for 30 test cases\n\n---\n\n## Troubleshooting\n\n### Error: \"Not in a Sip-AI project directory\"\n\n**Solution:** Navigate to the web app directory first:\n```bash\ncd /path/to/sip-ai\nsip-benchmark <command>\n```\n\n### Error: \"Missing required environment variables\"\n\n**Solution:** Ensure `.env.local` exists and contains:\n- `POSTGRES_URL`\n- `OPENAI_API_KEY`\n- `YOUTUBE_API_KEY`\n\n### Error: \"Failed to import backend modules\"\n\n**Solutions:**\n1. Ensure web app dependencies are installed: `npm install`\n2. Check that TypeScript files exist in `backend/` directory\n3. Verify you're using Node.js 18+\n\n### Progress bars not showing\n\n**Solution:** Ensure your terminal supports ANSI escape codes. Most modern terminals (iTerm2, Terminal.app, Windows Terminal) work fine.\n\n---\n\n## Advanced Usage\n\n### Custom Model/Temperature\n\n```bash\nsip-benchmark run \\\n  --benchmark-id abc123 \\\n  --model gpt-4o \\\n  --temperature 0.5\n```\n\n### Skip Persona Regeneration (Quick Debugging)\n\n```bash\nsip-benchmark run \\\n  --benchmark-id abc123 \\\n  --skip-persona-regen\n```\n\nThis skips persona generation and uses cached personas, saving ~2-3 minutes per run.\n\n### View All Benchmarks\n\n```bash\nsip-benchmark list\n```\n\n### Export Report Data\n\nReports are saved in `reports/` directory:\n- `benchmark-<run-id>.md` - Human-readable markdown\n- `benchmark-<run-id>.json` - Machine-readable JSON\n\n---\n\n## Development\n\n### Project Structure\n\n```\nsip-benchmark/\n├── bin/\n│   └── cli.js              # Executable entry point\n├── src/\n│   ├── cli.ts              # Commander.js CLI interface\n│   ├── backend-importer.ts # Dynamic backend loader\n│   ├── types.ts            # Type definitions\n│   └── commands/\n│       ├── run.ts          # Run benchmark command\n│       ├── setup.ts        # Setup benchmark command\n│       ├── list.ts         # List benchmarks command\n│       ├── menu.ts         # Interactive menu command\n│       └── report.ts       # View report command\n├── package.json\n├── tsconfig.json\n└── README.md\n```\n\n### Building\n\n```bash\nnpm run build\n```\n\nCompiles TypeScript to `dist/` directory.\n\n### Testing Locally\n\n```bash\ncd /path/to/sip-ai\nnpm run build  # Build the tool first\nnode /path/to/sip-benchmark/bin/cli.js list\n```\n\n---\n\n## Publishing (Optional)\n\n### Publish to npm\n\n```bash\ncd /path/to/sip-benchmark\nnpm login\nnpm publish\n```\n\nThen colleagues can install:\n```bash\nnpm install -g sip-benchmark\n```\n\n### Publish to Homebrew\n\n1. Create a formula\n2. Submit to `homebrew-core` or your own tap\n\n---\n\n## Support\n\nFor issues or questions:\n1. Check this README first\n2. Review web app's `scripts/benchmark/README.md` for detailed benchmark system docs\n3. Contact the team\n\n---\n\n## License\n\nMIT - Internal tool for Sip AI team\n","readmeFilename":"README.md"}